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Agent-based Computational Economics for Policy Analysis

Total Cost €


EC-Contrib. €






 ACEPOL project word cloud

Explore the words cloud of the ACEPOL project. It provides you a very rough idea of what is the project "ACEPOL" about.

systemic    dynamics    calibrated    standard    crises    emerged    equilibrium    theory    complementary    ready    statistical    strategies    agent    employing    plan    modeling    economics    properly    financial    computational    world    innovativeness    prominent    policy    external    interconnectedness    micro    additionally    mitigating    employed    calibration    learning    started    once    central    dynamic    banks    sectors    standards    massive    crisis    intervention    debt    methodological    econometric    dsge    negative    prepare    ante    avoiding    rigosously    descriptive    generating    innovative    ask    alternative    private    fellowship    techniques    directions    occupy    triggered    stochastic    ex    spread    algorithmic    tackling    post    possibly    evaluation    overhangs    exercises    hence    validation    closely    reconsideration    interventions    tool    economic    analyze    counterfactual    models    risk    profession    validated    public    datasets    ace    model    formal   

Project "ACEPOL" data sheet

The following table provides information about the project.


There are not information about this coordinator. Please contact Fabio for more information, thanks.

 Coordinator Country France [FR]
 Total cost 173˙076 €
 EC max contribution 173˙076 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2017
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2019
 Duration (year-month-day) from 2019-03-01   to  2021-02-28


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITE COTE D'AZUR FR (NICE) coordinator 173˙076.00


 Project objective

The recent economic crisis has also been a crisis for economic theory. Hence, the economic profession started to debate and prepare a methodological reconsideration about the general role of economic models; new modeling strategies, alternative and complementary to the standard Dynamic Stochastic General Equilibrium (DSGE) models, have therefore emerged. Among these innovative approaches, Agent-based Computational Economics (ACE) started to occupy a prominent role. However, ACE models still need to be improved in three main directions before being ready to be employed as a standard policy tool adopted by central banks. These three directions are: (i) calibration, (ii) external validation, (iii) formal evaluation of systemic risk.

This fellowship aims at directly tackling these three issues by employing new statistical learning, econometric, and algorithmic techniques and by applying them to an ACE model that enables one to analyze private and public debt dynamics by closely following the financial and real sectors at the micro-level.

The research plan here proposed aims at developing a calibrated and validated model able to explain how the rise in private debt and the interconnectedness of financial institutions might lead to financial crisis, which then might spread to the real sector and ask for a massive public sector intervention, possibly generating also public debt overhangs. Additionally, the innovativeness in the methods here employed will allow to establish higher standards for the development of descriptive ACE models. Once these model are properly and rigosously calibrated and validated by means of real-world datasets indeed, they can be adopted to evaluate a set of counterfactual policy exercises. In particular we aim at understanding which ex-ante policy measures might help avoiding debt-triggered crises and which ex-post policy interventions might help in mitigating their negative effects.

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The information about "ACEPOL" are provided by the European Opendata Portal: CORDIS opendata.

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